Risultati della ricerca - distributed evolution ((algorithm OR algorithmics) OR (algorithmics OR algorithmicsics))

Quantum Markov Chain Monte Carlo for Cosmological Functions di Sarracino, Giuseppe, Cardone, Vincenzo Fabrizio, Scaramella, Roberto, Riccio, Giuseppe, Bulgarelli, Andrea, Burigana, Carlo, Cappelli, Luca, Cavuoti, Stefano, Farsian, Farida, Graziotti, Irene, Meneghetti, Massimo, Murante, Giuseppe, Parmiggiani, Nicolò, Rizzo, Alessandro, Schillirò, Francesco, Testa, Vincenzo, Trombetti, Tiziana

Sommario: “... with an application to cosmological functions, to derive posterior distributions from cosmological probes...”
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A Conditional Abundance Matching Method of Extending Simulated Halo Merger Trees to Resolve Low-Mass Progenitors and Sub-halos di Chen, Yangyao, Mo, H. J., Li, Cheng, Wang, Kai, Wang, Huiyuan, Yang, Xiaohu

Sommario: “...We present an algorithm to extend subhalo merger trees in a low-resolution dark-matter-only...”
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Leveraging Analog Quantum Computing with Neutral Atoms for Solvent Configuration Prediction in Drug Discovery di D'Arcangelo, Mauro, Loco, Daniele, team, Fresnel, Gouraud, Nicolaï, Angebault, Stanislas, Sueiro, Jules, Monmarché, Pierre, Forêt, Jérôme, Henry, Louis-Paul, Henriet, Loïc, Piquemal, Jean-Philip

Sommario: “...We introduce quantum algorithms able to sample equilibrium water solvent molecules configurations...”
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Fast simulations of X-ray absorption spectroscopy for battery materials on a quantum computer di Fomichev, Stepan, Casares, Pablo A. M., Soni, Jay, Azad, Utkarsh, Kunitsa, Alexander, Voigt, Arne-Christian, Mueller, Jonathan E., Arrazola, Juan Miguel

Sommario: “... evolution error bound. The third is the choice of an optimized distribution of samples that takes advantage...”
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Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems di Karris, Nicholas, Nikitopoulos, Evangelos A., Kevrekidis, Ioannis G., Lee, Seungjoon, Cloninger, Alexander

Sommario: “...We develop an Euler-type method to predict the evolution of a time-dependent probability measure...”
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Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices di Berrisch, Jonathan, Ziel, Florian

Sommario: “... matrices and penalized smoothing. The new online learning algorithm generalizes the standard CRPS learning...”
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Classical Machine Learning: Seventy Years of Algorithmic Learning Evolution di Ezugwu, Absalom E., Ho, Yuh-Shan, Egwuche, Ojonukpe S., Ekundayo, Olufisayo S., Van Der Merwe, Annette, Saha, Apu K., Pal, Jayanta

Sommario: “.... This study provides a comprehensive overview of the evolution of traditional learning algorithms...”
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Pinching Antenna-Aided Wireless Powered Communication Networks di Li, Yixuan, Xu, Hongbo, Zeng, Ming, Liu, Yuanwei

Sommario: “...-complexity stochastic parameter differential evolution (SPDE) algorithm. Numerical results validate...”
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Improved Bounds for Context-Dependent Evolutionary Models Using Sequential Monte Carlo di Mathews, Joseph, Schmidler, Scott C.

Sommario: “... for a Markov chain Monte Carlo algorithm that samples the conditional distribution over latent sample...”
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Discovering Temporally-Aware Reinforcement Learning Algorithms di Jackson, Matthew Thomas, Lu, Chris, Kirsch, Louis, Lange, Robert Tjarko, Whiteson, Shimon, Foerster, Jakob Nicolaus

Sommario: “... learning algorithms parameterized by surrogate objective functions. To improve upon manually designed...”
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A convex approach for Markov chain estimation from aggregate data via inverse optimal transport di Mascherpa, Michele, Ringh, Axel, Taghvaei, Amirhossein, Karlsson, Johan

Sommario: “...We address the problem of identifying the dynamical law governing the evolution of a population...”
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Simulating Evolvability as a Learning Algorithm: Empirical Investigations on Distribution Sensitivity, Robustness, and Constraint Tradeoffs di Fidalgo, Nicholas, Ye, Puyuan

Sommario: “...The theory of evolvability, introduced by Valiant (2009), formalizes evolution as a constrained...”
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Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics di Gaitonde, Jason, Moitra, Ankur, Mossel, Elchanan

Sommario: “... distribution is intractable unless $\mathsf{NP}=\mathsf{RP}$, and moreover, any algorithm to learn from i.i.d...”
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Restarting the Numerical Flow Iteration through low rank tensor approximations di Wilhelm, Rostislav-Paul, Kormann, Katharina

Sommario: “... for the Vlasov--Poisson system. It stores the temporal evolution of the electric field and reconstructs...”
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Evolvable Conditional Diffusion di Wei, Zhao, Ooi, Chin Chun, Gupta, Abhishek, Wong, Jian Cheng, Chiu, Pao-Hsiung, Toh, Sheares Xue Wen, Ong, Yew-Soon

Sommario: “... function through updates to the descriptive statistic for the denoising distribution, and derive...”
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Measuring Epistemic Unfairness for Algorithmic Decision-Making di Quaresmini, Camilla, Piccinin, Lisa, Breschi, Valentina

Sommario: “... in algorithmic environments. First, we introduce a deficit-based template that models epistemic injustices...”
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Determining probability density functions with adiabatic quantum computing di Robbiati, Matteo, Cruz-Martinez, Juan M., Carrazza, Stefano

Sommario: “... to each other. In this work, we present a method for fitting one-dimensional probability distributions...”
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Optimal Quantum Likelihood Estimation di Levi, Alon, Ossi, Ziv, Cohen, Eliahu, Te'eni, Amit

Sommario: “...A hybrid quantum-classical algorithm is a computational scheme in which quantum circuits are used...”
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A Brief Survey of Formal Models of Concurrency di Averill, Charles

Sommario: “... algorithms, a cornerstone of networking, is a longstanding area of research in which models and frameworks...”
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Distributed Architecture Reconstruction of Polyglot and Multi-Repository Microservice Projects di Manglaras, Oscar, Farkas, Alex, Woolford, Thomas, Treude, Christoph, Wagner, Markus

Sommario: “... to maintain due to the rapid, independent evolution of services. While static architecture reconstruction...”
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